- Genetic Algorithm (GA)
- Local Search (SL)
- Iterated Local Search (ILS)
- Population Base Incremental Learning (PBIL)
- Simulated Annealing (SA)
- Tabu Search (TS)
- Artificial Bee Colony (ABC)
python main_KSP.py
python main_statis_KSP.py
python main.py
python main_statis.py
- Simulated annealing: From basics to applications (Daniel Delahaye, Supatcha Chaimatanan, Marcel Mongeau)
- Iterated Local Search: Framework and Applications (Helena Ramalhinho Lourenco, Thomas Stuzle, Olivier C Martin)
- An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics (Shumeet Baluja)
- An Efficient Algorithm for the Knapsack Sharing Problem (Mhand Hifi, Slim Sadfi, Abdelkader Shibi)
- An Overview of Genetic Algorithms: Part 1, Fundamentals (David Beasley, David R.Bull, Ralph R. Martin)
- Comparison of Metaheuristics (John Silberholz and Bruce Golden)
- Removing the Genetics from the Standard Genetic Algorithm
- Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems (Dervis Karaboga and Bahriye Basturk)
- Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem
- On the Neighborhood Structure of the Traveling Salesman Problem Generated by Local Search Moves (Günther Stattenberger, Markus Dankesreiter, Florian Baumgartner, Johannes J.Schneider)
- MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with time windows